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Proceedings Papers

Case Study: Predicting Electrical Submersible Pump Failures Using Artificial Intelligence and Physics-Based Hybrid Models

Shejuti Silvia, Yocheved Gilad, Thomas Andrew Wilson, Babak Akbari, Edward R. Furlong
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214462-MS
https://doi.org/10.2118/214462-MS
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Proceedings Papers

A Novel High-Speed AI-Physics Hybrid Model to Predict the Reservoir Behavior; A Case Study

Ali Qubian, Mohammed Ahmad Zekraoui, Sina Mohajeri, Emad Mortezazadeh, Reza Eslahi, Maryam Bakhtiari, Abrar Al Dabbous, Asma Al Sagheer, Ali Alizadeh, Mostafa Zeinali
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214475-MS
https://doi.org/10.2118/214475-MS
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View Paper titled, A Novel High-Speed AI-Physics Hybrid Model to Predict the Reservoir Behavior; A Case Study
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Proceedings Papers

Environomics Framework for Sustainable Business Practices: Industrial Case Studies on True Impact Reduction and Process Optimization Through AI

Abhijith Suboyin, Morgan Eldred, Jimmy Thatcher, Abdul Rehman, Ivan Gee, Hassaan Anjum
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214459-MS
https://doi.org/10.2118/214459-MS
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View Paper titled, Environomics Framework for Sustainable Business Practices: Industrial Case Studies on True Impact Reduction and Process Optimization Through AI
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Proceedings Papers

Enhancing Drilling Operations Through Edge Analytics: Evaluation of IIoT Architecture for Remote Rig Automation

Fahd Saghir, Tariq Qais, Maher Malibari, Yusef Alaas
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214477-MS
https://doi.org/10.2118/214477-MS
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View Paper titled, Enhancing Drilling Operations Through Edge Analytics: Evaluation of IIoT Architecture for Remote Rig Automation
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Proceedings Papers

Physics-Informed Neural Networks and Capacitance-Resistance Model: Fast and Accurate Oil and Water Production Forecast Using End-to-End Architecture

Elizaveta S. Gladchenko, Egor A. Illarionov, Denis M. Orlov, Dmitry A. Koroteev
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214461-MS
https://doi.org/10.2118/214461-MS
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View Paper titled, Physics-Informed Neural Networks and Capacitance-Resistance Model: Fast and Accurate Oil and Water Production Forecast Using End-to-End Architecture
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Proceedings Papers

Advisory System for Drilling Optimization Using Artificial Intelligence and In-Cutter Sensing Data

Alexis Koulidis, Shehab Ahmed
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214468-MS
https://doi.org/10.2118/214468-MS
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View Paper titled, Advisory System for Drilling Optimization Using Artificial Intelligence and In-Cutter Sensing Data
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Proceedings Papers

A Reinforcement Learning Approach for Real-Time Autonomous Decision-Making in Well Construction

Sahar Keshavarz, Petr Vita, Elmar Rueckert, Ronald Ortner, Gerhard Thonhauser
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214465-MS
https://doi.org/10.2118/214465-MS
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View Paper titled, A Reinforcement Learning Approach for Real-Time Autonomous Decision-Making in Well Construction
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Proceedings Papers

Leveraging AI for Inventory Management and Accurate Forecast – An Industrial Field Study

Morgan Edward Eldred, Jimmy Thatcher, Abdul Rehman, Ivan Gee, Abhijith Suboyin
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214457-MS
https://doi.org/10.2118/214457-MS
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View Paper titled, Leveraging AI for Inventory Management and Accurate Forecast – An Industrial Field Study
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Proceedings Papers

Application of Data-Mining Algorithms to Parameterize Static and Dynamic Models

Babatope O Kayode, Karl D Stephen, Abdullah Kaba
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214476-MS
https://doi.org/10.2118/214476-MS
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View Paper titled, Application of Data-Mining Algorithms to Parameterize Static and Dynamic Models
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Proceedings Papers

AI in Hydraulic Fracturing: The Journey from Guessing to Certainty

Thiago Machado, Adnan Mohammed
Paper presented at the SPE Symposium Leveraging Artificial Intelligence to Shape the Future of the Energy Industry, January 17–18, 2023
Paper Number: SPE-214463-MS
https://doi.org/10.2118/214463-MS
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View Paper titled, AI in Hydraulic Fracturing: The Journey from Guessing to Certainty
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Proceedings Papers

Modelling of Electric Submersible Pump Work on Gas-Liquid Mixture by Machine Learning

Kirill Alexandrovich Goridko, Arturas Rimo Shabonas, Rinat Alfredovich Khabibullin, Vladimir Sergeevich Verbitsky, Andrey Valeryevich Gladkov
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208661-MS
https://doi.org/10.2118/208661-MS
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View Paper titled, Modelling of Electric Submersible Pump Work on Gas-Liquid Mixture by Machine Learning
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Proceedings Papers

Generation of a Complete Profile for Porosity Log While Drilling Complex Lithology by Employing the Artificial Intelligence

Ahmed Al-Sabaa, Hany Gamal, Salaheldin Elkatatny
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208642-MS
https://doi.org/10.2118/208642-MS
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View Paper titled, Generation of a Complete Profile for Porosity Log While Drilling Complex Lithology by Employing the Artificial Intelligence
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Proceedings Papers

Unlocking the Potential of Electrical Submersible Pumps: the Successful Testing and Deployment of a Real-Time Artificially Intelligent System, for Failure Prediction, Run Life Extension, and Production Optimization

Mohammed Al Radhi, Fernando Angel Bermudez, Wael Al Madhoun, Khaled Al Blooshi, Noor Nasser Al Nahhas, Mohammed Nazeih Shono
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208647-MS
https://doi.org/10.2118/208647-MS
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View Paper titled, Unlocking the Potential of Electrical Submersible Pumps: the Successful Testing and Deployment of a Real-Time Artificially Intelligent System, for Failure Prediction, Run Life Extension, and Production Optimization
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Proceedings Papers

Discriminating Shale Layers by Pseudo CGR Logs Created Using Artificial Intelligence

Saud K. Aldajani, Saud F. Alotaibi, Abdulazeez Abdulraheem
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208663-MS
https://doi.org/10.2118/208663-MS
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View Paper titled, Discriminating Shale Layers by Pseudo CGR Logs Created Using Artificial Intelligence
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Proceedings Papers

Artificial Intelligence Adoption in Drilling Optimization: Guidelines for Successful System Configuration and User Onboarding

Andrew Creegan, Michael Roberts
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208638-MS
https://doi.org/10.2118/208638-MS
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View Paper titled, Artificial Intelligence Adoption in Drilling Optimization: Guidelines for Successful System Configuration and User Onboarding
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Proceedings Papers

Prediction of Gas Viscosity of Yemeni Gas Fields Using Machine Learning Techniques

Salman Sadeg Deumah, Wahib Ali Yahya, Abbas Mohamed Al-khudafi, Khaled Saeed Ba-Jaalah, Waleed Tawfeeq Al-Absi
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208667-MS
https://doi.org/10.2118/208667-MS
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View Paper titled, Prediction of Gas Viscosity of Yemeni Gas Fields Using Machine Learning Techniques
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Proceedings Papers

Evaluation of Machine Learning Methods for Prediction of Multiphase Production Rates

Anton Gryzlov, Liliya Mironova, Sergey Safonov, Muhammad Arsalan
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208648-MS
https://doi.org/10.2118/208648-MS
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Proceedings Papers

Creating Opportunities for Successful Artificial Intelligence Applications in the Upstream Petroleum Industry

Fatai Adesina Anifowose
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208875-MS
https://doi.org/10.2118/208875-MS
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View Paper titled, Creating Opportunities for Successful Artificial Intelligence Applications in the Upstream Petroleum Industry
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Proceedings Papers

Deep Learning Enabled Deblurring of Computed Tomography Images of Porous Media

Khalid Labib Alsamadony, Ertugrul Umut Yildirim, Guenther Glatz, Umair bin Waheed, Sherif M. Hanafy
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208665-MS
https://doi.org/10.2118/208665-MS
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View Paper titled, Deep Learning Enabled Deblurring of Computed Tomography Images of Porous Media
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Proceedings Papers

Application of Machine Learning in Gas-Hydrate Formation and Trendline Prediction

Celestine Udim Monday, Toyin Olabisi Odutola
Paper presented at the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, October 18–19, 2021
Paper Number: SPE-208653-MS
https://doi.org/10.2118/208653-MS
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View Paper titled, Application of Machine Learning in Gas-Hydrate Formation and Trendline Prediction
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